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Fetal growth restriction (FGR) is one of the leading causes of perinatal morbidity and mortality. Many studies have reported an association between FGR and fetal Doppler indices focusing on umbilical artery (UA), middle cerebral artery (MCA), and ductus venosus (DV). The uteroplacental-fetal circulation which affects the fetal growth consists of not only UA, MCA, and DV, but also umbilical vein (UV), placenta and uterus itself. Nevertheless, there is a paucity of large-scale cohort studies that have assessed the association between UV, uterine wall, and placental thickness with perinatal outcomes in FGR, in conjunction with all components of the uteroplacental-fetal circulation. Therefore, this multicenter study will evaluate the association among UV absolute flow, placental thickness, and uterine wall thickness and adverse perinatal outcome in FGR fetuses. This multicenter retrospective cohort study will include singleton pregnant women who undergo at least one routine fetal ultrasound scan during routine antepartum care. Pregnant women with fetuses having structural or chromosomal abnormalities will be excluded. The U-AID indices (UtA, UA, MCA, and UV flow, placental and uterine wall thickness, and estimated fetal body weight) will be measured during each trimester of pregnancy. The study population will be divided into two groups: (1) FGR group (pregnant women with FGR fetuses) and (2) control group (those with normal growth fetus). We will assess the association between U-AID indices and adverse perinatal outcomes in the FGR group and the difference in U-AID indices between the two groups. [ABSTRACT FROM AUTHOR]

The common marmoset (Callithrix jacchus) is considered an ideal species for developing genetically modified nonhuman primates (NHP) models of human disease, particularly eye disease. They have been proposed as a suitable bridge between rodents and other NHP models due to their similar ophthalmological features to humans. Prenatal ultrasonography is an accurate and reliable diagnostic tool for monitoring fetal development and congenital malformation. We monitored fetal eye growth and development using noninvasive ultrasonography in 40 heads of clinically normal fetuses during pregnancy to establish the criteria for studying congenital eye anomalies in marmosets. The coronal, sagittal, and transverse planes were useful to identify the facial structures for any associated abnormalities. For orbital measurements, biorbital distance (BOD), ocular diameter (OD), interorbital distance (IOD), and total axial length (TAL) were measured in the transverse plane and carefully identified for intraorbital structures. As a result, high correlations were observed between delivery‐based gestational age (GA) and biparietal diameter (BPD), BOD, OD, and TAL. The correlation assessments based on BOD provide more reliable results for monitoring eye growth and development in normal marmosets than any other parameters since BOD has the highest correlation coefficient according to both delivery‐based GA and BPD among ocular measurements. In conclusion, orbital measurements by prenatal ultrasonography provide reliable indicators of marmoset eye growth, and it could offer early diagnostic criteria to facilitate the development of eye disease models and novel therapies such as genome editing technologies in marmosets. Research highlights: Prenatal ultrasound was used to evaluate fetal growth and eye development in 40 clinically normal marmoset fetuses. It identified a high correlation between delivery‐based gestational age (GA) and parietal diameter (BPD), one of the biometrics for assessing fetal size. In addition, high correlations were observed between the delivery‐based GA and the ocular development biometrics, including biorbital distance (BOD), orbital diameter (OD), and total axial length (TAL).Correlation evaluation based on BOD provided more reliable results for monitoring eye development in normal marmosets since BOD has the highest correlation coefficient according to delivery‐based GA and BPD among ocular measurements.Prenatal ultrasonography is an easy and noninvasive method in marmosets and provides reliable results for evaluating fetal viability and eye growth. [ABSTRACT FROM AUTHOR]

This study uses convolutional neural networks (CNNs) and cardiotocography data for the real-time classification of fetal status in the mobile application of a pregnant woman and the computer server of a data expert at the same time (The sensor is connected with the smartphone, which is linked with the web server for the woman and the computer server for the expert). Data came from 5249 (or 4833) cardiotocography traces in Anam Hospital for the mobile application (or the computer server). 150 data cases of 5-minute duration were extracted from each trace with 141,001 final cases for the mobile application and for the computer server alike. The dependent variable was fetal status with two categories (Normal, Abnormal) for the mobile application and three categories (Normal, Middle, Abnormal) for the computer server. The fetal heart rate served as a predictor for the mobile application and the computer server, while uterus contraction for the computer server only. The 1-dimension (or 2-dimension) Resnet CNN was trained for the mobile application (or the computer server) during 800 epochs. The sensitivity, specificity and their harmonic mean of the 1-dimension CNN for the mobile application were 94.9%, 91.2% and 93.0%, respectively. The corresponding statistics of the 2-dimension CNN for the computer server were 98.0%, 99.5% and 98.7%. The average inference time per 1000 images was 6.51 micro-seconds. Deep learning provides an efficient model for the real-time classification of fetal status in the mobile application and the computer server at the same time. [ABSTRACT FROM AUTHOR]